Within a wireless network, there will typically be a plurality of nodes that need to communicate with each other, and wireless communications links are established between the various nodes to support such communications. Considering a wireless telecommunications network, for a downlink communication path a transmitter node (for example a base station (BS)) may need to communicate with a plurality of recipient nodes (such as mobile stations(MSs)/items of end user equipment(UEs)). Similarly, for an uplink communication path multiple transmitter nodes (for example MSs/UEs) may need to communicate with a particular recipient node (for example a BS).
Each transmitter node may provide one or more transmitters, and each transmitter may be formed of one or more physical antennas. For each antenna, electric signals are converted into electro-magnetic (radio) waves. One or more physical antennas may be grouped to form a logical antenna. For each logical antenna, a channel of wireless communication will be provided.
A wireless signal (such as a radio-frequency (RF) signal) traversing through such a wireless communication channel is subject to multiple reflections, diffractions and scattering effects. Hence, the original signal transmitted from a logical antenna will reach a destination receive antenna via multiple paths. The signal observed at the receive antenna will be the superimposition of the attenuated, phase shifted and delayed replicas of the original transmitted signal.
Channel estimation is a process used to characterise the effects of the channel, and typically a recipient node will include a channel estimator stage for generating channel state information (CSI), such CSI comprising channel estimates such as the per-path complex attenuation coefficients and path delays. In addition, the CSI may also comprise an error covariance matrix, providing a measure of the estimated accuracy of the channel estimates.
The CSI together with the wireless signal received over the channel are subsequently fed into a channel equaliser within the recipient node, which is responsible for reversing the effects of the multipath channel, seeking to restore the received signal to match as closely as possible to the original transmitted signal. The process of using the phase of the channel during equalisation is known as coherent detection.
Whilst it is possible to compute the CSI directly from the received signal, utilising the second and in some instances higher order statistics of the signal, the complexity of such a scheme is prohibitively high, requiring long processing periods to guarantee convergence with slow adaptation capabilities, making this scheme unsuitable for rapidly time-varying channels.
Many systems (including most telecommunication systems in service today) do not seek to compute the CSI directly from the received signal, but instead use pilot-aided channel estimation (PACE) techniques. PACE schemes rely on multiplexing the information bearing data with a known reference signal, the reference signal typically consisting of a number of symbols called pilots or reference symbols. The reference symbols are utilised by the receiver to compute channel estimates at the known locations of those reference symbols (often referred to as pilot locations) and then perform interpolation/prediction to estimate the channel at the data locations.
The accuracy of the channel estimates depends on the pilot density (the fraction of pilots to the total number of pilots and data symbols). As the pilot density increases, so does the quality of the channel estimates. However, increasing the pilot density has a detrimental effect on data throughput. In addition, channel estimation can also be improved by allocating more transmit power to the pilot symbols, but this comes at the expense of decreasing the signal to noise ratio for the data symbols. It is also well known that in certain types of radio channels, the pilot positions may also influence the quality of the channel estimates. Thus, there is a trade-off between the channel estimation accuracy and bandwidth efficiency.
Pilot design, i.e. the assignment of the pilot density, pilot locations and powers relative to data symbols, has been addressed in a variety of articles, for example:    1) L. Tong, B. M. Sadler and M. Dong, “Pilot-Assisted Wireless Transmission,” Signal Processing Magazine, IEEE, vol. 21, no. 6, pp. 12-25, 2004.    2) S. Adireddy, L. Tong and H. Viswanathan, “Optimal placement of training for frequency-selective block-fading channels,” Information Theory, IEEE Transactions on, vol. 48, no. 8, pp. 2338-2353, 2002.    3) X. Ma, L. Yang and G. B. Giannakis, “Optimal training for MIMO frequency-selective fading channels,” Wireless Communications, IEEE Transactions on, vol. 4, no. 2, pp. 453-466, 2005.
4) R. Negi and J. Cioffi, “Pilot tone selection for channel estimation in a mobile OFDM system,” Consumer Electronics, IEEE Transactions on, vol. 44, no. 3, pp. 1122-1128, 1998.    5) W. Zhang, X.-G. Xia and W.-K. Ma, “On the number of pilots for OFDM system in multipath fading channels,” Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on, vol. 4, pp. iv-381-iv-384, 2004.
As stated in article 1 above, the most commonly used design criteria for pilot-assisted transmission methods are based on
1. Information theoretic metrics (see articles 2 and 3),
2. Channel estimation (see article 4), or
3. Source estimation (see article 5).
Considering the information theoretic metrics approach, the Shannon capacity specifies the maximum rate across all possible transceiver designs at which information can be transmitted over a communication channel with an error probability that is arbitrary small assuming a sufficiently long code length. To make this metric more practical, the authors of the articles 2 and 3 constrained the channel estimator to be a linear minimum mean square error (MMSE) receiver, and then proceeded to link the mutual information with channel estimation and design training sequences that maximize a lower bound of the average mutual information for SISO (see article 2) and MIMO (see article 3) channels, respectively. For frequency-selective block fading channels in an orthogonal frequency division multiplexing (OFDM) system, these articles conclude that the optimal solution is to place the pilots equally apart using the same transmit power. Notwithstanding this powerful result, the information theoretic framework used by these articles fails to capture the system performance for practical coding and modulation schemes (MCS) used in wireless systems to generate the information bearing signal transmitted over the channel in combination with the pilot symbols.
The second approach identified above, namely the channel estimation approach, relies on deriving the channel estimates as a function of the pilots, and either minimise the Cramer-Rao bound (CRB) or the MMSE (see article 4) on the estimates. Not surprisingly, the same results as the previous method were obtained. Finally, the third and final method for pilot design was presented in article 5, where a closed-form solution of the average BER (bit error rate) as a function of the pilot spacing was found. The BER derived in article 5 is also for an OFDM system, but is only applicable for QPSK modulated signals. Higher order modulations are not considered, and most importantly coding is completely ignored.
The above approaches for pilot design hence have a number of limitations. In particular, they seek to optimise one particular sub-block of the receiver chain, namely the channel estimation block, but do not take account of the modulation and coding scheme intended to be used to transmit the data over the channel. However, the robustness of the information bearing signal to the channel effects will vary significantly dependent on the modulation and coding scheme used for the data. Accordingly such known pilot design techniques may provide a higher channel estimation accuracy than is actually necessary having regards to the modulation and coding scheme to be used for the data, and as mentioned earlier an increase in the channel estimation accuracy will generally have a detrimental effect on bandwidth efficiency, and accordingly will adversely affect throughput.
Further, in a real-world environment, the channel effects experienced within a channel will vary over time, and it would be desirable to provide a technique which could adapt the pilot design as necessary in order to compensate for such time varying effects.